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Opiniones y comentarios de aprendices correspondientes a Bayesian Statistics: Techniques and Models por parte de Universidad de California en Santa Cruz

416 calificaciones
132 reseña

Acerca del Curso

This is the second of a two-course sequence introducing the fundamentals of Bayesian statistics. It builds on the course Bayesian Statistics: From Concept to Data Analysis, which introduces Bayesian methods through use of simple conjugate models. Real-world data often require more sophisticated models to reach realistic conclusions. This course aims to expand our “Bayesian toolbox” with more general models, and computational techniques to fit them. In particular, we will introduce Markov chain Monte Carlo (MCMC) methods, which allow sampling from posterior distributions that have no analytical solution. We will use the open-source, freely available software R (some experience is assumed, e.g., completing the previous course in R) and JAGS (no experience required). We will learn how to construct, fit, assess, and compare Bayesian statistical models to answer scientific questions involving continuous, binary, and count data. This course combines lecture videos, computer demonstrations, readings, exercises, and discussion boards to create an active learning experience. The lectures provide some of the basic mathematical development, explanations of the statistical modeling process, and a few basic modeling techniques commonly used by statisticians. Computer demonstrations provide concrete, practical walkthroughs. Completion of this course will give you access to a wide range of Bayesian analytical tools, customizable to your data....

Principales reseñas

31 de oct. de 2017

This course is excellent! The material is very very interesting, the videos are of high quality and the quizzes and project really helps you getting it together. I really enjoyed it!!!

14 de feb. de 2021

The course was really interesting and the codes were easy to follow. Although I did take the previous course for this series, I still found it hard to grasp the concepts immediately.

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76 - 100 de 133 revisiones para Bayesian Statistics: Techniques and Models

por Jayanand S

16 de sep. de 2019

Complex subject made easy with easy to understand theory & practical examples

por Víthor R F

9 de abr. de 2018

Very cool, probably the best course I've done in Coursera. Keep rocking! :)

por Gustavo M

26 de ago. de 2019

Very nice course. A bit more theory on sampling methods would be welcome.

por Alejandro D O

13 de may. de 2020

Excellent, balanced (theory and practice) course. I enjoyed very much.

por Peter W

8 de ago. de 2020

Very pleased with the course. It was well worth the time and effort.

por Nicholas W T

6 de sep. de 2018

Very thorough instruction. Excellent feedback and support on forums.

por Ahmed M

12 de nov. de 2018

If you want to become good in modelling it is recommended to enrol.

por Razik R M T

14 de ene. de 2021

Great explanations. The instructor made it so easy to understand.

por Emma S

20 de nov. de 2020

I absolutely loved this course! Challenging and interesting!

por Stephen B

29 de may. de 2019

Best course done to date. I wish they had one in STAN too!

por nicole s

7 de nov. de 2017

A great course, very detailed and a very good instructor!

por Paramita C

28 de feb. de 2021

The material was excellent and the videos were awesome!

por Ilia S

24 de sep. de 2018

I found this course very interesting and informative.

por Ken A

27 de ene. de 2020

Excellent course. Streamlined but extremely useful.

por Hsiaoyi H

31 de jul. de 2018

Great course to learn both theories and techniques!

por Anuj K P

1 de ago. de 2020


por Arkobrato G

11 de nov. de 2019

Great course with challenging assignments and de

por Enrique A

7 de nov. de 2020

Thanks Teacher Matthew Heiner, Thanks Coursera.

por Lau C

15 de abr. de 2019

Super clear and easy to follow. Thanks so much.

por Tibor R

20 de abr. de 2019

Very good and useful course, and hard as well.

por Victor Z

30 de jul. de 2018

A very good practical and theoretical course

por Farrukh M

25 de jul. de 2017

I appropriate the way the course is taught.


19 de oct. de 2020

Very nice course, simple and comprehensive

por pritam s

24 de jul. de 2021

I have learned a lot from this course

por Evgenii L

2 de may. de 2018

A very good course to introduce yours